code: def test_simultaneous_cb():
      # The exact numbers here are regression tests, but they are close
      # to page 103 of Klein and Moeschberger.
  
      df = bmt.loc[bmt["Group"] == "ALL", :]
      sf = SurvfuncRight(df["T"], df["Status"])
      lcb1, ucb1 = sf.simultaneous_cb(transform="log")
      lcb2, ucb2 = sf.simultaneous_cb(transform="arcsin")
  
      ti = sf.surv_times.tolist()
      ix = [ti.index(x) for x in (110, 122, 129, 172)]
      assert_allclose(
          lcb1[ix], np.r_[0.43590582, 0.42115592, 0.4035897, 0.38785927]
      )
      assert_allclose(
          ucb1[ix],
          np.r_[0.93491636, 0.89776803, 0.87922239, 0.85894181],
      )
  
      assert_allclose(
          lcb2[ix],
          np.r_[0.52115708, 0.48079378, 0.45595321, 0.43341115],
      )
      assert_allclose(
          ucb2[ix],
          np.r_[0.96465636, 0.92745068, 0.90885428, 0.88796708],
      )
  
imports: import os
  import numpy
  from statsmodels.duration.survfunc import SurvfuncRight, survdiff, plot_survfunc, CumIncidenceRight
  from numpy.testing import assert_allclose
  import pandas
  import pytest
label_desc: Use image node_id 5 for calling a global function with example usage: test_simultaneous_cb() without return types